mlsanityData to 14 Oct 2026

Policy Gradient for Coherent Risk Measures

arXiv 1502.03919 ↗First posted 13 Feb 2015cs.AI cs.LG stat.MLcited by 76

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Cited by 28 in Deep reinforcement learning methods, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

Several authors have recently developed risk-sensitive policy gradient methods that augment the standard expected cost minimization problem with a measure of variability in cost. These studies have focused on specific risk-measures, such as the variance or conditional value at risk (CVaR). In this work, we extend the policy gradient method to the whole class of coherent risk measures, which is widely accepted in finance and operations research, among other fields. We consider both static and time-consistent dynamic risk measures. For static risk measures, our approach is in the spirit of policy gradient algorithms and combines a standard sampling approach with convex programming. For dynamic risk measures, our approach is actor-critic style and involves explicit approximation of value function. Most importantly, our contribution presents a unified approach to risk-sensitive reinforcement learning that generalizes and extends previous results.

Key facts. Cited by 76 papers in the map (data through 14 Oct 2026). First posted on arXiv 13 Feb 2015.

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Citing papers per year: 2018: 1; 2019: 0; 2020: 0; 2021: 13; 2022: 10; 2023: 8; 2024: 9; 2025: 15; 2026: 20.

76 papers.

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  1. 2021Recent Advances in Reinforcement Learning in Financecited by 110
  2. 2022Efficient Risk-Averse Reinforcement Learningcited by 43
  3. 2021RMIX: Learning Risk-Sensitive Policies for Cooperative Reinforcement Learning Agentscited by 31
  4. 2023Policy Gradient for Rectangular Robust Markov Decision Processescited by 31
  5. 2022Challenging Common Assumptions in Convex Reinforcement Learningcited by 30
  6. 2021Risk-Averse Bayes-Adaptive Reinforcement Learningcited by 29
  7. 2021Off-Policy Risk Assessment in Contextual Banditscited by 29
  8. 2022One Risk to Rule Them All: A Risk-Sensitive Perspective on Model-Based Offline Reinforcement Learningcited by 23
  9. 2021Reinforcement Learning with Dynamic Convex Risk Measurescited by 21
  10. 2021On the Convergence and Optimality of Policy Gradient for Markov Coherent Riskcited by 20
  11. 2021Robust Risk-Aware Reinforcement Learningcited by 18
  12. 2023Soft Robust MDPs and Risk-Sensitive MDPs: Equivalence, Policy Gradient, and Sample Complexitycited by 17
38 more
  1. 2018Risk-Sensitive Generative Adversarial Imitation Learningcited by 16
  2. 2024A Reductions Approach to Risk-Sensitive Reinforcement Learning with Optimized Certainty Equivalentscited by 16
  3. 2025A Survey of Safe Reinforcement Learning and Constrained MDPs: A Technical Survey on Single-Agent and Multi-Agent Safetycited by 13
  4. 2023Risk-Averse Model Uncertainty for Distributionally Robust Safe Reinforcement Learningcited by 12
  5. 2024CIMRL: Combining IMitation and Reinforcement Learning for Safe Autonomous Drivingcited by 12
  6. 2025Fast and Robust: Task Sampling with Posterior and Diversity Synergies for Adaptive Decision-Makers in Randomized Environmentscited by 12
  7. 2023Distributional Model Equivalence for Risk-Sensitive Reinforcement Learningcited by 9
  8. 2022Off-Policy Risk Assessment in Markov Decision Processescited by 7
  9. 2023A Cubic-regularized Policy Newton Algorithm for Reinforcement Learningcited by 7
  10. 2025Risk-Averse Finetuning of Large Language Modelscited by 7
  11. 2025Efficient Risk-sensitive Planning via Entropic Risk Measurescited by 7
  12. 2026ALOE: Action-Level Off-Policy Evaluation for Vision-Language-Action Model Post-Trainingcited by 7
  13. 2021Policy Gradient Methods for Distortion Risk Measurescited by 6
  14. 2022A Risk-Sensitive Approach to Policy Optimizationcited by 6
  15. 2024Risk-Sensitive Soft Actor-Critic for Robust Deep Reinforcement Learning under Distribution Shiftscited by 6
  16. 2021Planning for Risk-Aversion and Expected Value in MDPscited by 5
  17. 2025Near-Optimal Sample Complexity for Iterated CVaR Reinforcement Learning with a Generative Modelcited by 5
  18. 2025Recursive Entropic Risk Optimization in Discounted MDPs: Sample Complexity Bounds with a Generative Modelcited by 5
  19. 2026Towards trustworthy agentic AI: a comprehensive survey of safety, robustness, privacy, and system securitycited by 5
  20. 2022RASR: Risk-Averse Soft-Robust MDPs with EVaR and Entropic Riskcited by 4
  21. 2022Non-stationary Risk-sensitive Reinforcement Learning: Near-optimal Dynamic Regret, Adaptive Detection, and Separation Designcited by 4
  22. 2021Deep Reinforcement Learning for Equal Risk Pricing and Hedging under Dynamic Expectile Risk Measurescited by 3
  23. 2025DR-SAC: Distributionally Robust Soft Actor-Critic for Reinforcement Learning under Uncertaintycited by 3
  24. 2021Risk-Averse Decision Making Under Uncertaintycited by 2
  25. 2021ACReL: Adversarial Conditional value-at-risk Reinforcement Learningcited by 2
  26. 2022A policy gradient approach for optimization of smooth risk measurescited by 2
  27. 2022Tailoring to the Tails: Risk Measures for Fine-Grained Tail Sensitivitycited by 2
  28. 2023Is Risk-Sensitive Reinforcement Learning Properly Resolved?cited by 2
  29. 2024Inverse Concave-Utility Reinforcement Learning is Inverse Game Theorycited by 2
  30. 2025Risk-Averse Constrained Reinforcement Learning with Optimized Certainty Equivalentscited by 2
  31. 2026Frictive Policy Optimization for LLMs: Epistemic Intervention, Risk-Sensitive Control, and Reflective Alignmentcited by 2
  32. 2026Actor-Critic Algorithm for Dynamic Expectile and CVaRcited by 2
  33. 2023Learning Rewards to Optimize Global Performance Metrics in Deep Reinforcement Learningcited by 1
  34. 2024Risk-Sensitive Multi-Agent Reinforcement Learning in Network Aggregative Markov Gamescited by 1
  35. 2024Physics-informed RL for Maximal Safety Probability Estimationcited by 1
  36. 2024On the Approximation and Convergence of Distributional Policy Gradient Algorithms for Risk-Sensitive Reinforcement Learningcited by 1
  37. 2025Uncertainty-Aware Strategies: A Model-Agnostic Framework for Robust Financial Optimization through Subsamplingcited by 1
  38. 2025Ethics-Aware Safe Reinforcement Learning for Rare-Event Risk Control in Interactive Urban Drivingcited by 1

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